Explore the vast range of titles available.

Green credit policy (GCP), as one of the key financial instruments to achieve ’carbon peaking’ and ‘carbon neutrality’ targets, provides capital support for the green development of enterprises. This paper explores the impact mechanism of GCP on the sustainability performance of heavily polluting enterprises (HPEs) from the perspectives of technological innovation level (TIL) and credit resource allocation (CRA), using panel data for Chinese A-share listed manufacturing companies from 2010 to 2015 to construct a propensity score matching and differences-in-differences (PSM-DID) model. We find that GCP has a causal effect on corporate sustainability performance (CSP). Although GCP significantly improves CSP, there is no long-term effect. Heterogeneity analysis shows that the relationship between GCP and CSP is only significant in non-state-owned enterprises and in eastern and low-market-concentration enterprises. Mechanism tests indicate that GCP stimulates HPEs to invest more in technological innovation and thereby improves CSP through the innovation compensation effect; the credit constraint and information transfer effects caused by GCP reduce the credit resources available to HPEs but have a significant forced effect on CSP. This paper enriches the study of the economic consequences of GCP and provides implications for stakeholders to improve the green financial system and achieve green transformation of HPEs.

In 2020, China’s R&D investment reached 2442.6 billion RMB, and it ranks second in the world, but the performance of green innovation has not proportionately improved. The question of how to promote the improvement of green innovation performance is particularly important in order to mitigate future environmental problems and issues due to rapid development of China’s economy. While past research has examined the relationship between R&D investment and green innovation, they have not explicitly considered the effect of regional technological innovation level on this relationship. Hence, we fill this gap by exploring the relationship between R&D investment and green innovation performance using data from various regions in China from 2015 to 2019, under the effect of a threshold variable, namely, technological innovation. We explore the impact of economic development level, environmental regulation level, foreign direct investment, and science and technology in fiscal expenditures on green innovation performance. The empirical results show that when the regional technological innovation level is used as the threshold variable, the R&D investment has a significant double-threshold effect with the lagging three-phase green innovation performance. When the technological innovation level is low (< 0.1082), R&D investment has a negative impact on green innovation performance. Moreover, when the technological innovation level is high (>0.5837), the impact of regional R&D investment on green innovation performance is sub-optimal. Consequently, the range of [0.1082 to 0.5837] is the best range for the positive impact of R&D investment on green innovation performance. Furthermore, among China’s 30 provinces and cities, 24% (mostly areas located in the southwest and northeast of China) have the technological innovation level in the optimal range. Our results help explain the current status of China's R&D investment and green innovation development, and provide a theoretical basis for the formulation of government innovation investment policies.

Green and sustainable development is unstoppable. The digital economy has driven great changes in production methods and has become a key strength in reshaping global economic structure and achieving sustainable development. Cities are both the mainstay of economic growth and the main source of various environmental pollution problems. Therefore, studying the relationship between urban digital economy and urban green total factor productivity is of great significance. Based on panel data from 252 cities in China 2011–2019, a two-way fixed effects model was used to examine the impact of urban digital economy on urban green total factor productivity. The empirical results indicate that: (1) Urban digital economy has a significant positive impact on urban green total factor productivity. (2) Urban technological-innovation-level and human-capital-structure of play a mediating role in the impact. (3) This impact has regional heterogeneity and resource-based type heterogeneity. The research conclusions are not only valuable supplements to previous research, but also providing reliable instructions for implementing a flexible digital economy policy.

Financial development makes many contributions to promoting economic growth. With the deterioration of the ecological environment, scholars have begun to consider the role of financial development in sustainable economic development. This paper investigates the influence of financial development on China’s energy environmental performance (EEP) by utilizing panel data from 2002 to 2017. The findings demonstrate that financial development has a significant impact on regional EEP, and the results remain robust through a series of assessments. The technological innovation level and human capital are the transmission paths through which financial development affects regional EEP. Furthermore, using the difference-in-differences (DID) method, we not only prove the causal relationship between financial development and EEP but also show that the allocation of financial assets can significantly affect energy consumption efficiency. Finally, heterogeneity analysis shows that financial development has varying impacts on energy efficiency in distinct regions across China. The influence of financial development on EEP displays a clear “Matthew Effect”. To the best of our knowledge, our findings offer greater insight into the energy-saving and emission-reduction effects of financial development.

Marine fisheries scientific and technological innovation level (MFSTIL) drives the modernization and sustainability of China’s fisheries. Based on the panel data of 11 coastal provinces and cities in China from 2011 to 2022, the article used the entropy weight-TOPSIS method, spatial econometric model (Standard Deviation Ellipse), Dagum Gini coefficient, Markov modified grey prediction model and other methods to analyze the spatiotemporal differentiation of China’s MFSTIL and its future development trend. The results show that: (1) China’s MFSTIL was generally good and grew steadily year by year from 2011 to 2022, but regional development was uneven; (2) The temporal evolution of MFSTIL has a sequence of “slow rise-rapid rise-steady rise”, and the differentials between regions also fluctuate upward; (3) The spatial pattern of MFSTIL is uneven in distribution, and there are “lagging areas” in the three major marine economic zones; in terms of evolution, it has the dynamic equilibrium characteristics of “northeast-southwest”, and the center of gravity of the standard deviation ellipse moves first to the northeast and then to the southwest; (4) The overall spatial variation in MFSTIL has increased year by year in recent years, with hyper-variance density contributing most significantly to regional differences; (5) The MFSTIL will maintain the growth trend of the previous 12 years in 2023-2030, and the ranking of provinces will change slightly. The gap between the northern and eastern regions will narrow, while their disparity with the southern region will widen, the absolute gap between regions cannot be ignored. In this regard, the article proposed following suggestions: (1) Implement targeted support strategies through special funds and the construction of industry-academia-research integration platforms to identify and empower regions lagging behind in innovation, thereby stimulating local scientific research and innovation capabilities; (2) Optimize the spatial layout of the three major marine economic zones, build integrated industrial chains, and achieve complementary regional development; (3) Establish a dynamic monitoring and early warning system based on big data and the Internet of Things to achieve real-time monitoring of resources, the environment, markets, and industries, thereby promoting sustainable and balanced development.

Based on panel data from 36 cities in Northeast China spanning the years 2012 to 2021, this study employs the dual dimensions of “commonality” and “prosperity” to holistically assess the level of common prosperity. By developing a bidirectional panel fixed-effect model, this research conducts an empirical examination of the positive influence exerted by the expansion of higher education in Northeast China on achieving common prosperity. The findings indicate that the expansion of higher education in the region significantly contributes to the attainment of the common prosperity goal. In cities characterized by a high level of economic development and significant growth in higher education, this expansion markedly fosters common prosperity. Moreover, the quality of higher education and the level of scientific and technological innovation play a substantial positive moderating role in the process of advancing common prosperity through the expansion of higher education in Northeast China. Consequently, this study proposes several recommendations. Firstly, the expansion of higher education in Northeast China should shift from a focus on “quantitative growth” to one of “integration and quality enhancement.” Secondly, it is imperative to focus on the regions where higher education development is lagging and implement relevant strategies to optimize the layout of higher education in Northeast China. Thirdly, the quality of higher education should be improved to promote the realization of common prosperity through high-quality education. Lastly, the impact of higher education expansion on promoting common prosperity can be enhanced by optimizing the discipline structure, introducing new emerging disciplines, and deepening scientific and technological innovation. Plain language summary Research Background: This study focuses on the expansion of higher education scale in the Northeast region of China, exploring its relationship with the goal of achieving common prosperity. Panel data from 36 cities in the Northeast region of China from 2012 to 2021 are used to assess how the expansion of higher education impacts the process of achieving common prosperity. Research Purpose: The purpose is to examine the impact of the expansion of higher education in the Northeast region on the realization of common prosperity and to analyze the role of technological innovation and educational quality in this process. Research Method: The study employs a two-way panel fixed-effect model, comprehensively assessing the level of common prosperity by considering the two dimensions of “commonality” and “prosperity.” Research Conclusion: The study finds that the expansion of higher education in the Northeast region significantly promotes the realization of common prosperity. In cities with higher levels of economic development and rapid growth in higher education, this expansion has a particularly significant role in promoting common prosperity. At the same time, the quality of higher education and the level of scientific and technological innovation play a significant positive moderating role in the relationship between the expansion of higher education and common prosperity. Research Recommendations: 1. The development of higher education in the Northeast region should shift from quantitative expansion to the enhancement of quality and connotation. 2. Pay heed to the regions where the development of higher education is weak and optimize the layout of higher. 3. Improve the quality of education to drive the realization of common prosperity through high-quality education. 4. Enhance the contribution of higher education to promoting common prosperity by optimizing the disciplinary structure, introducing emerging disciplines, and deepening scientific.

Global population aging trends are intensifying, presenting multifaceted economic and social challenges for countries worldwide. As the world’s largest developing country, China has entered a phase of extreme demographic aging, posing significant questions about its impact on the ongoing upgrading of industrial structures. How does this demographic shift influence the upgrading of industrial structures, and does technological innovation mitigate or exacerbate this impact? The empirical results indicate that population aging impedes upgrading the industrial structure, while technological innovation positively affects the relationship between the two. Moreover, using technological innovation as a threshold variable, the impact of population aging on industrial structure upgrading evolves in a “gradient” manner from “impediment” to “insignificant” to “promotion” as the technological innovation levels increase. These findings offer practical guidance for tailoring industrial policies to different stages of technological advancement.

Basic research is the driver of advanced productivity and is an important guarantee for the market competitiveness of enterprise. In order to understand the influence of basic research on the development of China’s digital economy industry, this paper, based on structural equation model by collecting data from 209 enterprises in digital economy industry, explores the relationship between enterprise participation in basic research and four factors: enterprise efficiency, perceived risk, priority, and technological innovation, together with function mechanism. The results show that, first enterprises can improve efficiency, reduce potential risk concerns, and enhance technology level by expanding business revenue, enlarging scale, and upgrading R&D institutions, thus promoting participation in basic research. At the same time, the government can provide more subsidies for enterprise R&D funds to reduce enterprise concern about the risk of basic research, and guide them to expand their investment in R&D and focus on basic research so as to expand their participation in this field. Secondly, the optimization of enterprise participation in basic research, the upgrading of R&D institutions and the number of invention patents have mutually-reinforced effect, while the expansion of enterprise scale help to reduce the constraint of return risk to a certain extent. Finally, this paper proposes some policies and suggestions to enhance enterprise participation in basic research from the perspective of promoting industrial development and social equity.

This fascinating and controversial text makes sense of the complexities of research in the workplace and how 'working' knowledge is constructed. Featuring experts from Britain, Japan, North America and Australia, it is an outstanding contribution to the literature of Human Resource Management (HRM). It's interdisciplinary approach addresses key issues and debates such as:* the influences of new technology, language, power, culture and gender upon the 'construction' of knowledge* the impact of globalization* working knowledge into the 21st century* practice and performance implications.It's outlook, geared towards the 21st century, makes it essential reading for researchers, teachers and students within HRM, policy-makers and all those concerned with professional development.